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James Sacco
Bioinformatics Scientist
Department of Gene and Cell Therapy
ASC Therapeutics
Milpitas, CA, 95035
Independent, self-motivated bioinformatics scientist, with five years of experience in cancer immunotherapy and gene therapy for rare diseases. Specialist in computational biology of CRISPR gene editing. An analytical thinker and quick learner, with experience in next-generation sequencing (NGS) methods, especially RNA-Seq, and construction of reproducible and robust analysis pipelines. Integrated genotype phenotype data to predict disease severity. Developed machine learning applications to analyze population-scale genomic and real-world patient data. Experienced with cross-functional teams of diverse cultural and technical backgrounds.
Employment
Bioinformatics Scientist
ASC Therapeutics
Milpitas, CA
Present - 2021
● Support NGS experiments to quantify and characterize on/off-targets of gene modifications by performing data wrangling and analysis, using open-source methods (e.g., CALITAS, CHANGE-Seq, CRISPResso2, GUIDE-Seq, Cas-OFFinder) and custom scripts.
● Query, retrieve, and integrate data from public genomics databases, to characterize alignments between CRISPR target sequences and guide RNAs.
● Compare concordance and sensitivity of five CRISPR off-target detection methods.
● Spearhead implementation of reproducible, robust bioinformatics data practices
Biomarker Data Analyst
Genentech
South San Francisco, CA
2020 - 2019
● Established department-first machine learning pipeline to study effects of biomarker operations on quality of cancer immunotherapy assays.
● Generated over ten percent annual operation cost reduction via analysis of vendor performance over twenty clinical sites.
● Upgraded data operations for six data streams, including flow cytometry, biomarker operations, and oncology data warehouses.
● Monitored and solved sample data quality issues for two clinical trial arms.
Data Curator
Genentech
South San Francisco, CA
2019 - 2018
● Collaborated with AI engineers to create an ETL pipeline for multi-modal survival prediction and patient stratification, by using Python machine learning and R/Bioconductor to integrate gene panel and RNA-Seq data.
● Tested and refined a textual entity and geolocation matching pipeline for clinical trial site management, resulting in over 90% accuracy.
● Designed ETL data pipeline for integration of real-world EHRs into deep learning module, using Python, SQL, and Apache Spark.
● Organized and managed close coordination of gRED Artificial Intelligence, data management, and DevOps functions, to bring clinical machine learning from prototype to production.
Data Curator, Bioinformatics Analyst
BioMarin Pharmaceutical
San Rafael, CA
2018 - 2017
● Established an integrated genetic and curated literature workflow to predict incidence and prevalence rates of over sixty rare, genetic disorders, with R statistical and visualization packages (ggplot2) and MATLAB.
● Upgraded and tested RNA-Seq data pipeline (STAR2, SAMtools, Bioconductor) to discern disease contribution of rare variants to neural disease.
● Spearheaded development of three relational databases derived from Hail HPC population genomics platform, in collaboration with software engineer.
● Co-authored manuscript submitted to peer-reviewed publication, on prediction of disease severity in metachromatic leukodystrophy.
Research Associate
University of Miami Miller School of Medicine, The Miami Project to Cure Paralysis Pearse Lab
Miami, FL
2017 - 2016
● Mentored research associates in developing bioinformatic skills, specifically in multiple sequence alignment and standard molecular biological protocols (restriction enzyme digestion, gel electrophoresis, spectrophotometry).
● Identified over forty putative conserved vertebrate phosphodiesterase proteins, by using multiple sequence alignment and genomic evidence.
Education
Rowan University, Graduate School of Biomedical Sciences
Master of Biomedical Science
Stratford, NJ
Florida International University, The Honors College
BSc, Biological Sciences
Miami, FL
Publications & Posters
Prediction of disease severity in metachromatic leukodystrophy using measures of protein activity and a novel phenotype matrix.
American Society of Human Genetics. [Forthcoming on bioRxiv.org; pending acceptance in PLoS Genetics]
N/A
2020
M. Trinidad, X. Hong, J. Sacco, H.P. Nguyen, W.T. Clark, S. Froelich, J.H. LeBowitz, M.H. Gelb.
Association of HGMD and gnomAD variants of unknown significance with prediction of disease incidence and prevalence.
Annual BioMarin Research Conference. [Poster]
N/A
2018
J. Sacco, W.T. Clark, K. Yu, K. Wu, J.H. LeBowitz.
Regulating Axonal Responses to Injury: The Intersection between Signaling Pathways Involved in Axon Myelination and The Inhibition of Axon Regeneration.
Frontiers in Molecular Neuroscience. 2016 Jun 8;9:33.
N/A
2016
Rao S.N., Pearse D.D. Acknowledgement
Languages
English: Native
Spanish: Native
Disclaimer
This resume was made with the R package pagedown and datadrivencv.
Code available on GitHub.
Last updated on 2022-01-19.The most recent version of this resume is available here.